Búsqueda Imágenes Maps Play YouTube Noticias Gmail Drive Más »
Iniciar sesión
Usuarios de lectores de pantalla: deben hacer clic en este enlace para utilizar el modo de accesibilidad. Este modo tiene las mismas funciones esenciales pero funciona mejor con el lector.

Patentes

  1. Búsqueda avanzada de patentes
Número de publicaciónUS20090082651 A1
Tipo de publicaciónSolicitud
Número de solicitudUS 12/315,449
Fecha de publicación26 Mar 2009
Fecha de presentación3 Dic 2008
Fecha de prioridad8 Mar 2004
También publicado comoCA2557240A1, CA2557240C, CN1929779A, EP1729631A1, EP1729631B1, EP2260758A2, EP2260758A3, EP2260758A9, US7194293, US7474907, US7890154, US8560036, US9211090, US20050197549, US20070208242, US20110092785, US20140031652, WO2005087095A1
Número de publicación12315449, 315449, US 2009/0082651 A1, US 2009/082651 A1, US 20090082651 A1, US 20090082651A1, US 2009082651 A1, US 2009082651A1, US-A1-20090082651, US-A1-2009082651, US2009/0082651A1, US2009/082651A1, US20090082651 A1, US20090082651A1, US2009082651 A1, US2009082651A1
InventoresClark R. Baker, Jr.
Cesionario originalNellcor Puritan Bennett Llc, Nellcor Puritan Bennett Incorporated
Exportar citaBiBTeX, EndNote, RefMan
Enlaces externos: USPTO, Cesión de USPTO, Espacenet
Selection of ensemble averaging weights for a pulse oximeter based on signal quality metrics
US 20090082651 A1
Resumen
A method and a system for ensemble averaging signals in a pulse oximeter, including receiving first and second electromagnetic radiation signals from a blood perfused tissue portion corresponding to two different wavelengths of light, obtaining an assessment of the signal quality of the electromagnetic signals, selecting weights for an ensemble averager using the assessment of signal quality, and ensemble averaging the electromagnetic signals using the ensemble averager.
Imágenes(3)
Previous page
Next page
Reclamaciones(20)
1. A method of ensemble averaging signals in a pulse oximeter, comprising:
receiving, via a sensor, first and second electromagnetic radiation signals from a blood perfused tissue portion corresponding to two different wavelengths of light; and
using an oximeter,
obtaining an assessment of the signal quality of the electromagnetic signals;
calculating weights for an ensemble averager from a continuous weighting function based at least in part upon the assessment of signal quality; and
ensemble averaging the electromagnetic signals using the ensemble averager.
2. The method of claim 1, wherein the obtaining an assessment of the signal quality comprises obtaining a measure of a degree of arrhythmia of the signals.
3. The method of claim 2, wherein the obtaining an assessment of the signal quality further comprises obtaining a measure of a degree of similarity or correlation between the first and second electromagnetic radiation signals.
4. The method of claim 1, wherein the obtaining an assessment of the signal quality comprises obtaining a measure of a degree of motion artifact present in the signals.
5. The method of claim 4, wherein the obtaining a measure of the degree of motion artifact comprises obtaining a ratio of a current pulse amplitude to a long-term average pulse amplitude of the signals.
6. The method of claim 1, wherein the obtaining an assessment of the signal quality comprises obtaining a ratio of a current pulse amplitude to a previous pulse amplitude of the signal.
7. The method of claim 1, wherein the obtaining an assessment of the signal quality comprises obtaining a measure of a degree of the overall signal quality metric for a single pulse, which comprises a combination of other metrics.
8. The method of claim 1, wherein the obtaining an assessment of the signal quality comprises obtaining a ratio of a current pulse period to an average pulse period of the signals.
9. The method of claim 1, wherein the calculating weights comprises forming a combination of one or more parameters comprising a measure of a degree of arrhythmia of the signals, a measure of the degree of similarity or correlation between the first and second electromagnetic radiation signals, a measure of a degree of motion artifact by obtaining a ratio of a current pulse amplitude to a long-term average pulse amplitude of the signals, a ratio of a current pulse amplitude to a previous pulse amplitude of the signal, and/or a ratio of a current pulse period to an average pulse period of the signals.
10. A pulse oximetry system, comprising:
a sensor capable of receiving first and second electromagnetic signals from a blood perfused tissue portion corresponding to two different wavelengths of light; and
a pulse oximeter capable of:
obtaining an assessment of a signal quality of the first and second electromagnetic signals;
calculating a first weight associated with the first and second electromagnetic signals for an oxygen saturation ensemble averager and/or calculating a second weight associated with the first and second electromagnetic signals for a pulse rate ensemble averager using at least one continuously variable weighting function based at least in part upon the assessment of the signal quality; and
calculating an oxygen saturation value with an oxygen saturation averager based on the first weight and the first and second electromagnetic signals and/or calculating a pulse rate value with the pulse rate ensemble averager based at least in part upon the second weight and the first and second electromagnetic signals.
11. The pulse oximetry system of claim 10, wherein the pulse oximeter is capable of obtaining the assessment of the signal quality at least in part by determining a correlation between the first and second electromagnetic radiation signals.
12. The pulse oximetry system of claim 10, wherein the pulse oximeter is capable of measuring a degree of variability of a ratio-of-ratios of the first and second electromagnetic signals to obtain the assessment of the signal quality.
13. The pulse oximetry system of claim 10, wherein the first weight is based at least in part upon a variability of a ratio-of-ratios over a time.
14. The pulse oximetry system of claim 1, wherein the first weight is based at least in part upon a pulse qualification score.
15. The pulse oximetry system of claim 10, wherein the pulse oximeter is capable of normalizing the first and second electromagnetic signals.
16. The pulse oximetry system of claim 10, comprising a filter capable of low pass filtering the first and second electromagnetic signals.
17. A pulse oximetry system, comprising:
a sensor capable of receiving first and second electromagnetic signals from a blood perfused tissue portion corresponding to two different wavelengths of light; and
a pulse oximeter capable of:
obtaining an assessment of a signal quality of the first and second electromagnetic signals, wherein the assessment comprises a determination of whether arrhythmia is present;
calculating a weight associated with the first and second electromagnetic signals for an ensemble averager using at least one continuously variable weighting function based at least in part upon the assessment of the signal quality; and
calculating an oxygen saturation value with the ensemble averager based at least in part upon the determination of whether arrhythmia is present, the weight, and the first and second electromagnetic signals.
18. The pulse oximetry system of claim 17, wherein the pulse oximetry system is capable of reducing a degree of ensemble-averaging when arrhythmia is present.
19. The pulse oximetry system of claim 17, wherein the ensemble averager comprises a pulse rate ensemble averager and/or an oxygen saturation ensemble averager.
20. The pulse oximetry system of claim 17, wherein the weight is based in part on a variability of a ratio-of-ratios over a time.
Descripción
  • [0001]
    This application is a Continuation of U.S. patent application Ser. No. 11/701,173, filed on Feb. 1, 2007, which is a continuation of U.S. patent application Ser. No. 10/796,559, filed on Mar. 8, 2004, now U.S. Pat. No. 7,194,293 issued Mar. 20, 2007, the full disclosures of which are hereby incorporated by reference in their entirety.
  • BACKGROUND OF THE INVENTION
  • [0002]
    The present invention relates in general to oximeters, and in particular to the selection of ensemble averaging weights used for ensemble averaging of signals that include detected waveforms from a pulse oximeter.
  • [0003]
    A pulse oximeter is typically used to measure various blood characteristics including the blood oxygen saturation of hemoglobin in arterial blood and the pulse rate of the patient. Measurement of these characteristics has been accomplished by use of a non-invasive sensor that passes light through a portion of a patient's blood perfused tissue and photo-electrically senses the absorption and scattering of light in such tissue. The amount of light absorbed and scattered is then used to estimate the amount of blood constituent in the tissue using various algorithms known in the art. The “pulse” in pulse oximetry comes from the time varying amount of arterial blood in the tissue during a cardiac cycle. The signal processed from the sensed optical measurement is the familiar plethysmographic waveform, which corresponds with the cyclic attenuation of optical energy through a portion of a patient's blood perfused tissue.
  • [0004]
    Ensemble averaging, which is a temporal averaging scheme, involves the use of weighting factors. In a pulse oximeter, ensemble averaging is used to calculate a weighted average of new samples and previous ensemble-averaged samples from one pulse-period earlier. Weights selected and/or used for ensemble averaging have a significant effect on the ensemble averaging process. Such weights may be uniformly selected, or they may be based on the characteristics of the signals that are being ensemble averaged. For example, the Conlon U.S. Pat. No. 4,690,126 discloses ensemble averaging where different weights are assigned to different pulses and a composite, averaged pulse waveform is used to are assigned to different pulses and a composite, averaged pulse waveform is used to calculate oxygen saturation. Conlon's signal metrics for adjusting ensemble-averaging weights are based on a measure of the degree of motion artifact, a measure of the degree of low perfusion (e.g., pulse amplitude below a threshold), and pulse rate.
  • [0005]
    However, it is desirable to provide a more flexible and more robust methodology for the selection of ensemble averaging weights used for ensemble averaging of signals that include detected waveforms from a pulse oximeter.
  • BRIEF SUMMARY OF THE INVENTION
  • [0006]
    The present invention is directed to the selection of ensemble averaging weights used for ensemble averaging of signals that correspond with detected waveforms from a pulse oximeter. The selection of ensemble averaging weights are based on one or more or a combination of various signal quality metrics or indicators. In one embodiment, the present invention provides a method of ensemble averaging signals in a pulse oximeter. The method includes receiving first and second electromagnetic radiation signals from a blood perfused tissue portion corresponding to two different wavelengths of light; obtaining an assessment of the signal quality of the electromagnetic signals; selecting weights for an ensemble averager using the assessment of signal quality; and ensemble averaging the electromagnetic signals using the ensemble averager.
  • [0007]
    In one aspect, the selection of ensemble averaging weights involves an assessment and use of various signal quality indicators, where the selecting of weights includes forming a combination of one or more of the following signal quality parameters, namely: a measure of the degree of arrhythmia of the signals; a measure of the degree of similarity or correlation between the first and second electromagnetic radiation signals; a measure of the degree of motion artifact by obtaining a ratio of a current pulse amplitude to the long-term average pulse amplitude of the signals; a ratio of a current pulse amplitude to the previous pulse amplitude of the signal; and a ratio of a current pulse period to that of an average pulse period of the signals.
  • [0008]
    For a fuller understanding of the nature and advantages of the embodiments of the present invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • [0009]
    FIG. 1 is a block diagram of an exemplary oximeter.
  • [0010]
    FIG. 2 is a block diagram of the signal processing architecture of a pulse oximeter in accordance with one embodiment of the present invention.
  • DETAILED DESCRIPTION OF THE INVENTION
  • [0011]
    The methods and systems in accordance with the embodiments of the present invention are directed towards the selection of ensemble averaging weights used for ensemble averaging of signals that correspond with detected waveforms from a pulse oximeter. The selection of ensemble averaging weights are based on one or more or a combination of various signal quality metrics or indicators. The embodiments of the present invention are particularly applicable to and will be explained by reference to measurements of oxygen saturation of hemoglobin in arterial blood and pulse or heart rate, as in pulse oximeter monitors and pulse oximetry sensors. However, it should be realized that the embodiments of the present invention are equally applicable to any generalized patient monitor and associated patient sensor, such as ECG, blood pressure, etc., and are thus also applicable to non oximetry or pulse oximetry devices.
  • [0012]
    A typical pulse oximeter measures two physiological parameters, percent oxygen saturation of arterial blood hemoglobin (SpO2 or sat) and pulse rate. Oxygen saturation can be estimated using various techniques. In one common technique, the photocurrent generated by the photo-detector is conditioned and processed to determine the ratio of modulation ratios (ratio of ratios) of the red to infrared (IR) signals. This modulation ratio has been observed to correlate well to arterial oxygen saturation. Pulse oximeters and sensors may be empirically calibrated by measuring the modulation ratio over a range of in vivo measured arterial oxygen saturations (SaO2) on a set of patients, healthy volunteers, or animals. The observed correlation is used in an inverse manner to estimate blood oxygen saturation (SpO2) based on the measured value of modulation ratios of a patient. The estimation of oxygen saturation using modulation ratios is described in U.S. Pat. No. 5,853,364, entitled “METHOD AND APPARATUS FOR ESTIMATING PHYSIOLOGICAL PARAMETERS USING MODEL-BASED ADAPTIVE FILTERING,” issued Dec. 29, 1998, and U.S. Pat. No. 4,911,167, entitled “METHOD AND APPARATUS FOR DETECTING OPTICAL PULSES,” issued Mar. 27, 1990, which are both herein incorporated by reference in their entirety for all purposes. The relationship between oxygen saturation and modulation ratio is described, for example, in U.S. Pat. No. 5,645,059, entitled “MEDICAL SENSOR WITH MODULATED ENCODING SCHEME,” issued Jul. 8, 1997, which is herein incorporated by reference in its entirety for all purposes. Most pulse oximeters extract the plethysmographic signal having first determined saturation or pulse rate, both of which are susceptible to interference.
  • [0013]
    FIG. 1 is a block diagram of one embodiment of a pulse oximeter that may be configured to implement the embodiments of the present invention. The embodiments of the present invention may be implemented as a data processing algorithm that is executed by the microprocessor 122, described below. Light from light source 110 passes into a blood perfused tissue 112, and is scattered and detected by photodetector 114. A sensor 100 containing the light source and photodetector may also contain an encoder 116 which provides signals indicative of the wavelength of light source 110 to allow the oximeter to select appropriate calibration coefficients for calculating oxygen saturation. Encoder 116 may, for instance, be a resistor.
  • [0014]
    Sensor 100 is connected to a pulse oximeter 120. The oximeter includes a microprocessor 122 connected to an internal bus 124. Also connected to the bus is a RAM memory 126 and a display 128. A time processing unit (TPU) 130 provides timing control signals to light drive circuitry 132 which controls when light source 110 is illuminated, and if multiple light sources are used, the multiplexed timing for the different light sources. TPU 130 also controls the gating-in of signals from photodetector 114 through an amplifier 133 and a switching circuit 134. These signals are sampled at the proper time, depending upon which of multiple light sources is illuminated, if multiple light sources are used. The received signal is passed through an amplifier 136, a low pass filter 138, and an analog-to-digital converter 140. The digital data is then stored in a queued serial module (QSM) 142, for later downloading to RAM 126 as QSM 142 fills up. In one embodiment, there may be multiple parallel paths of separate amplifier, filter and A/D converters for multiple light wavelengths or spectra received.
  • [0015]
    Based on the value of the received signals corresponding to the light received by photodetector 114, microprocessor 122 will calculate the oxygen saturation using various algorithms. These algorithms require coefficients, which may be empirically determined, corresponding to, for example, the wavelengths of light used. These are stored in a ROM 146. In a two-wavelength system, the particular set of coefficients chosen for any pair of wavelength spectra is determined by the value indicated by encoder 116 corresponding to a particular light source in a particular sensor 100. In one embodiment, multiple resistor values may be assigned to select different sets of coefficients. In another embodiment, the same resistors are used to select from among the coefficients appropriate for an infrared source paired with either a near red source or far red source. The selection between whether the near red or far red set will be chosen can be selected with a control input from control inputs 154. Control inputs 154 may be, for instance, a switch on the pulse oximeter, a keyboard, or a port providing instructions from a remote host computer. Furthermore, any number of methods or algorithms may be used to determine a patient's pulse rate, oxygen saturation or any other desired physiological parameter.
  • [0016]
    The brief description of an exemplary pulse oximeter set forth above, serves as a basis for describing the methods for adjusting ensemble averaging weights for an ensemble averager, which are described below, in conjunction with FIG. 2.
  • [0017]
    The embodiments of the present invention may be implemented as a part of a larger signal processing system used to process optical signals for the purposes of operating a pulse oximeter. Such a signal processing system is shown in FIG. 2, which is a block diagram 200 of a signal processing architecture of a pulse oximeter in accordance with one embodiment of the present invention. The signal processing architecture 200 in accordance with the embodiments of the present invention may be implemented as a software algorithm that is executed by a processor of a pulse oximeter. In addition to calculating oxygen saturation and pulse rate, the system 200 measures various signal metrics that are used to determine filter weighting coefficients. Signal metrics are things that indicate if a pulse is likely a plethysmograph or noise. Signal metrics may be related to, for example, frequency (is it in the range of a human heart rate), shape (is it shaped like a cardiac pulse), rise time, etc. The system shown in FIG. 2 calculates both the oxygen saturation, and the pulse rate. The system 200 is also used for detecting venous pulsation and sensor off and lost pulse conditions, which are described separately below.
  • [0018]
    I. Oxygen Saturation Calculation
  • [0019]
    Block 202 represents the operation of the Signal Conditioning block. The digitized red and IR signals or waveforms are received and are conditioned in this block by: (1) taking the 1st derivative to get rid of baseline shift, (2) low pass filtering with fixed coefficients, and (3) dividing by a DC value to preserve the ratio. The function of the Signal Conditioning subsystem is to emphasize the higher frequencies that occur in the human plethysmograph and to attenuate low frequencies in which motion artifact is usually concentrated. The Signal Conditioning subsystem selects its filter coefficients (wide or narrow band) based on hardware characteristics identified during initialization. Inputs to block 202 are digitized red and IR signals, and its outputs are pre-processed red and IR signals.
  • [0020]
    Block 204 represents the operation of the Pulse Identification and Qualification block. The low pass filtered digitized red and IR signals are provided to this block to identify pulses, and qualify them as likely arterial pulses. This is done using a pre-trained neural net, and is primarily done on the IR signal. The pulse is identified by examining its amplitude, shape and frequency. An input to this block is the average pulse period from block 208. This function changes the upfront qualification using the pulse rate. The output of block 204 indicates the degree of arrhythmia and individual pulse quality. Inputs to block 204 are: (1) pre-processed red and IR signals, (2) Average pulse period, and (3) lowpass waveforms from the low pass filter. Outputs from block 204 include: (1) degree of arrhythmia, (2) pulse amplitude variations, (3) individual pulse quality, (4) pulse beep notification, and (5) qualified pulse periods and age.
  • [0021]
    Block 206 is used to compute signal quality metrics. This block (block 206) determines the pulse shape (e.g., derivative skew), period variability, pulse amplitude and variability, Ratio of Ratios variability, and frequency content relative to pulse rate. Inputs to block 206 include: (1) raw digitized red and IR signals, (2) degree of arrhythmia, individual pulse quality, pulse amplitude variation, (3) pre-processed red and IR signals, and (4) average pulse period. Outputs from block 206 include: (1) lowpass and ensemble averaging filter weights, (2) metrics for sensor off detector, (3) normalized pre-processed waveforms, and (4) percent modulation.
  • [0022]
    Block 208 computes average pulse periods. This block (block 208) calculates the average pulse period from the pulses received. Inputs to block 208 include: qualified pulse periods and age. An output from block 208 includes the average pulse period.
  • [0023]
    Block 210 represents the functioning of the lowpass filter and ensemble averaging subsystem. Block 210 low pass filters and ensemble averages normalized and preprocessed waveforms processed by block 206. The weights for the low pass filter are determined by the Signal Metrics block 206. The signal is also ensemble averaged (i.e., frequencies other than those of interest near the pulse rate and its harmonics are attenuated), with the ensemble averaging filter weights also determined by Signal Metrics block 206. Less weight is assigned if the signal is flagged as degraded. More weight is assigned if the signal is flagged as arrhythmic because ensemble-averaging is not appropriate during arrhythmia. Red and IR waveforms are processed separately, but with the same filtering weights. The filtering is delayed (e.g., approximately one second) to allow the signal metrics to be calculated first.
  • [0024]
    The filters use continuously variable weights. If samples are not to be ensemble-averaged, then the weighting for the previous filtered samples is set to zero in the weighted average, and the new samples are still processed through the algorithm. This block tracks the age of the signal and/or the accumulated amount of filtering (e.g., sum of response times and delays in processing). Too old a result will be flagged, if good pulses haven't been detected for a while. The inputs to block 210 include: (1) normalized pre-processed red and IR signals, (2) average pulse period, (3) low pass filter weights and ensemble averaging filter weights, (4) ECG triggers, if available, and (5) IR fundamental, for zero-crossing triggers. Outputs from block 210 include: (1) filtered red and IR signals, and (2) age.
  • [0025]
    Block 212 represents operations that estimate the ratio-of-ratios variance for the filtered waveforms and calculate averaging weights. The variable weighting for the filter is controlled by the ratio-of-ratios variance. The effect of this variable-weight filtering is that the ratio-of-ratios changes slowly as artifact increases and changes quickly as artifact decreases. The subsystem has two response modes, including fast and normal modes. For example, filtering in the fast mode targets an age metric of 3 seconds, and the target age may be 5 seconds in the normal mode. In the fast mode, the minimum weighting of the current value is clipped at a higher level. In other words, a low weight is assigned to the newest ratio-of-ratios calculation if there is noise present, and a high weight if no noise is present. The inputs to block 212 include: (1) filtered red and IR signals and age, (2) calibration coefficients, and (3) response mode (e.g., user speed settings). Outputs from block 212 include an averaging weight for ratio-of-ratios calculation. The averaging weight is used as an input to block 214 along with filtered IR and Red waveforms to calculate averaged ratio of ratios and age.
  • [0026]
    Block 216 represents operations that calculate oxygen saturation. Saturation is calculated using an algorithm with the calibration coefficients and averaged ratio of ratios. Inputs to block 116 include: (1) Averaged Ratio-of-Ratios, and (2) calibration coefficients. An output from block 216 is the oxygen saturation value.
  • [0027]
    II. Pulse Rate Calculation
  • [0028]
    Block 218 low pass filters and ensemble averages the signal(s) conditioned by block 202, for the pulse rate identification. The weights for the low pass filter are determined by the Signal Metrics block 206. The signal is also ensemble averaged (i.e., frequencies other than those of interest near the pulse rate and its harmonics are attenuated), with the ensemble averaging filter weights also determined by Signal Metrics block 206. Less weight is assigned if the signal is flagged as degraded. More weight is assigned if the signal is flagged as arrhythmic because ensemble-averaging is not appropriate during arrhythmia. Red and IR are processed separately. The filtering is delayed (e.g., approximately one second) to allow the signal metrics to be calculated first.
  • [0029]
    The filters use continuously variable weights. If samples are not to be ensemble-averaged, then the weighting for the previous filtered samples is set to zero in the weighted average, and the new samples are still processed through the algorithm. This block (block 218) tracks the age of the signal and/or the accumulated amount of filtering (sum of response times and delays in processing). Too old a result will be flagged (if good pulses haven't been detected for awhile). Inputs to block 218 include: (1) pre-processed red and IR signals, (2) average pulse period, (3) lowpass filter weights and ensemble averaging filter weights, (4) ECG triggers, if available, and (5) IR fundamental, for zero-crossing triggers. Outputs from block 218 include: (1) filtered red and IR signals and (2) age.
  • [0030]
    Block 220, or the Filtered Pulse Identification and Qualification block, calculates the pulse periods from the filtered waveforms, and its results are used only when a pulse is disqualified by block 204. Inputs to block 220 include: (1) filtered red and IR signals and age, (2) average pulse period, (3) hardware ID or noise floor, (4) and the kind or type of sensor that is used to detect the IR and Red energies. Output from block 220 includes qualified pulse periods and age.
  • [0031]
    Block 222, or the Average Pulse Periods and Calculate Pulse Rate block, calculates the pulse rate and average pulse period. This block (block 222) receives qualified pulse periods and age as inputs and provides: (1) average pulse period and (2) pulse rate as outputs.
  • [0032]
    III. Venous Pulsation
  • [0033]
    Block 224, or the Detect Venous Pulsation block receives as inputs the pre-processed red and IR signals and age from Block 202, and pulse rate and provides an indication of venous pulsation as an output. Block 224 also provides an IR fundamental waveform in the time domain using a single-tooth comb filter which is output to the Ensemble Averaging filters (e.g., block 210 and 218). Inputs to block 224 include: (1) filtered red and IR signals and age and (2) pulse rate. Outputs from block 124 include: an indication of venous pulsation and IR fundamental. In one embodiment, block 224 measures the “openness” of an IR-Red Lissajous plot to determine the whether a flag (e.g., Venous_Pulsation) should be set. The output flag (e.g., Venous_Pulsation) is updated periodically (e.g., every second). In addition, the IR fundamental waveform is output to the Ensemble Averaging filters.
  • [0034]
    IV. Sensor Off
  • [0035]
    Block 226, or the Detect Sensor-Off and Loss of Pulse Amplitude block, uses a pre-trained neural net to determine whether the sensor is off the surface of the blood-perfused tissue, for example, of a patient. The inputs to the neural net are metrics that quantify several aspects of the behavior of the IR and Red values over the last several seconds. Samples are ignored by many of the system 200's subsystems while the signal state is either not indicative of a pulse being present, or indicative that a sensor is not on a monitoring site (e.g., Pulse Present, Disconnect, Pulse Lost, Sensor May be Off, and Sensor Off). Inputs to block 226 include: (1) signal quality metrics, and (2) the oximeter's LED brightness, amplifier gain, and (3) an ID indicating the oximeter's hardware configuration. Outputs from block 226 include a signal state including sensor-off indication.
  • [0036]
    In the architecture 200 described above, the function of block 226, Pulse lost and Pulse Search indications, may be derived using information from several parts of the signal processing architecture. In addition, the signal processing architecture will not use the received IR and red waveforms to compute oxygen saturation or pulse rate if a valid sensor is not connected, or if the Sensor-Off or Loss of Pulse Amplitude are detected by the signal processing architecture.
  • [0037]
    The brief description of an embodiment of a pulse oximeter signal processing architecture in accordance with the present invention, set forth above, serves as a basis for describing the methods and devices that are directed towards the selection of ensemble averaging weights used for ensemble averaging of signals that correspond with detected waveforms from a pulse oximeter, as is generally indicated by blocks 210 and 218 above.
  • Ensemble Averaging Weights
  • [0038]
    As set forth above, the selection of ensemble averaging weights are based on one or more or a combination of various signal quality metrics or indicators. In particular, in one embodiment, the metrics that are used to adjust ensemble-averaging weight, includes a measure of the degree of arrhythmia. This metric is used to reduce the degree of ensemble-averaging when the patient appears to be arrhythmic, as ensemble-averaging works less well for signals having highly variable frequency content. Another metric used to adjust ensemble-averaging weight includes a measure of the degree of variability of ratio-of-ratios (e.g., lack of similarity or correlation between IR and Red waveforms). This metric is sensitive to the presence of motion or other noise sources. This metric is different from that of other known techniques such as Conlon's, in that Conlon teaches a metric that compares the similarity between current and previous-pulse waveforms, presumably from the same wavelength, but not the similarity between two simultaneous waveforms at different wavelengths. Another metric used to adjust ensemble-averaging weight includes a ratio of a current pulse amplitude to the long-term average pulse amplitude. A long-term average pulse amplitude refers to an average that has a response time of perhaps a minute when all pulses are qualified, and several times longer if most pulses are being disqualified. This metric is designed to capture the degree of motion artifact, similar to Conlon's, however, this metric is an analog metric, whereas Conlon's metric has just a few discrete states (e.g., no artifact, low artifact, high artifact). Another metric used to adjust ensemble-averaging weight includes a ratio of a current pulse amplitude to the previous pulse amplitude. This metric is used to quickly change the ensemble-averaging weight when large motion artifact start or stop. Another metric used to adjust ensemble-averaging weight includes a measure of the overall signal quality metric for a single pulse, which metric is itself a combination of several other metrics, including the metrics described above. This metric is used to quickly reduce the ensemble filtering when motion artifact subsides and the input waveform is presumed to be of better quality than a heavily ensemble-averaged waveform. Another metric used to adjust ensemble-averaging weight includes a ratio of a current pulse period to the average pulse period. This metric is used to reduce the ensemble filtering in the event that the heart skips a beat, which can happen occasionally on many people.
  • [0039]
    When the subsystem (210 and/or 218) is notified that the Pulse Identification and Qualification subsystem (204) has just completed evaluation of a potential pulse, the subsystem updates ensemble-averaging weights, used by the instances of the Ensemble Averaging subsystem. Separate weights are computed for the two Ensemble Averaging instances whose outputs are used in computing saturation and pulse rate. These weights are based in part on metrics provided by the instance of the Pulse Identification and Qualification subsystem whose input waveforms have not been ensemble averaged.
  • [0040]
    The equations for Sat_Ensemble_Averaging_Filter_Weight are as follows:
  • [0000]

    x=max(Short_RoR_Variance,Pulse_Qual_RoR_Variance/1.5)*max(Long_Term_Pulse_Amp_Ratio,1.0)
  • [0000]

    RoR_Variance_Based_Filt_Wt=0.5*0.05/max(0.05,x)
  • [0000]

    Arr_Prob=(Period_Var−0.1*Short_RoR_Variance−0.09)/(0.25−0.09);
  • [0000]

    Arr_Min_Filt_Wt_For_Sat=0.05+0.5*bound(Arr_Prob,0,1.0)
  • [0000]

    Sat_Ensemble_Averaging_Filter_Weight=max(RoR_Variance_Based_Filt_Wt,Arr_Min_Filt_Wt_For_Sat)*(1.0+Pulse_Qual_Score)
  • [0000]

    Sat_Ensemble_Averaging_Filter_Weight=min(Sat_Ensemble_Averaging_Filer Weight,1.0),
  • [0000]
    where bound(a,b,c) denotes min(max(a,b),c)
  • [0041]
    The above equations result in a default weight of 0.5 for low values of the Ratio-of-Ratios variances. Short_RoR_Variance and Pulse_Qual_RoR_Variance are both computed over a time interval (e.g., a three-second interval). The interval for Pulse_Qual_RoR_Variance ends with the qualification or rejection of the most recent pulse, which would usually include the most recent samples. The weight is reduced by high Ratio-of-Ratios variances, and by high values of Long_Term_Pulse_Amp_Ratio that would typically indicate motion artifact. Arr_Min_Filt_Wt_For_Sat imposes a minimum value on the ensemble-averaging weight (range 0.05-0.55) based primarily on Period_Var, which quantifies the degree of arrhythmia. This is done because ensemble-averaging is less effective for pulses having dissimilar periods. If the most recent pulse received a good Pulse_Qual_Score, this can increase the maximum value of Sat_Ensemble_Averaging_Filter_Weight from 0.5 to 1.0.
  • [0042]
    The equations for Rate_Ensemble_Averaging_Filter_Weight are as follows:
  • [0000]

    Arr_Prob=(Period_Var−0.07)/(0.20−0.07)
  • [0000]

    Arr_Min_Filt_Wt_For_Rate=0.05+0.5*bound(Arr_Prob,0,1.0)
  • [0000]

    x=max(RoR_Variance_Based_Filt_Wt,Arr_Min_Filt_Wt_For_Rate)*(1.0+Pulse_Qual_Score)
  • [0000]

    if Short_Term_Pulse_Amp_Ratio*Long_Term_Pulse_Amp_Ratio<1.0
  • [0000]

    x=x/Short_Term_Pulse_Amp_Ratio
  • [0000]

    if Avg_Period>0
  • [0000]

    x=x*bound(Pulse_Qual_Score*Qualified_Pulse_Period/Avg_Period,1.0,3.0)
  • [0000]

    Rate_Ensemble_Averaging_Filter_Weight=min(x,1.0)
  • [0043]
    These equations differ from the ones for Sat_Ensemble_Averaging_Filter. Weight as follows:
    • a) The thresholds used to compute Arr_Prob are somewhat lower, because it is desirable that arrhythmic pulses not be obscured by ensemble averaging prior to pulse qualification.
    • b) Small values of Short_Term_Pulse_Amp_Ratio typically indicate that motion artifact has just subsided, which means that the ensemble-averaging weight may be quickly increased. This has been found empirically to be beneficial for pulse qualification, but not for ratio-of-ratios filtering and saturation computation.
    • c) If the heart skips a beat, with or without prior arrhythmia, the longer-than-average Qualified_Pulse_Period that results will increase the ensemble-averaging weight, so as not to obscure the skipped beat from subsequent pulse qualification.
  • [0047]
    In one aspect, the ensemble averaging weights that have been determined as described above, are used for two separate ensemble averagers for processing a detected waveform for use in calculating oxygen saturation and a pulse rate. The ensemble averager used for calculating oxygen saturation operates on a signal which has been normalized, while the ensemble averager for the pulse rate calculation operates on a signal which has not been normalized. A pulse oximeter with separate ensemble averaging for oxygen saturation and heart rate is described in a co-pending patent application assigned to the assignee herein, and titled: Pulse Oxiemter with Separate Ensemble Averaging for Oxygen Saturation and Heart Rate, Attorney Docket: TTC-009103-022700US, is hereby incorporated herein by reference, in its entirety for all purposes. In that patent application, the metrics chosen for the two paths through the two ensemble averagers can be varied to optimize the ensemble averaging for oxygen saturation or pulse rate calculations. For example, a lower threshold is used for a metric to detect arrhythmic pulses when used to calculate pulse rate, as compared to calculating oxygen saturation. Also, a metric for a short term pulse amplitude ratio will be small when motion artifact has just subsided, and this is given more weight in the pulse rate calculation than in the oxygen saturation calculation.
  • DEFINITIONS
  • [0048]
    Data Inputs
  • [0049]
    Avg_Period—Average pulse period reported by Pulse Rate Calculation subsystem.
  • [0050]
    Long_Term_Pulse_Amp_Ratio—Quantifies last pulse amplitude compared to historic pulse amplitude. Provided by the Pulse Identification and Qualification subsystem. Values substantially larger than 1.0 are typically indicative of motion artifact, and result in lower Ensemble_Averaging_Filter_Weights.
  • [0051]
    Period_Var—Period-variability metric from the Pulse Identification and Qualification subsystem. Used to gauge the extent of arrhythmia. For instance, a value of 0.10 would indicate that the average difference between consecutive pulse periods is 10% of Avg_Period.
  • [0052]
    Pulse_Qual_RoR_Variance—RoR_Variance metric from the Pulse Identification and Qualification subsystem.
  • [0053]
    Pulse_Qual_Score—Score computed by the pulse qualification neural net in the Pulse Identification and Qualification subsystem. Zero is extremely poor and 1.0 is excellent.
  • [0054]
    Qualified_Pulse_Period—Most recent pulse period qualified by the Pulse Identification and Qualification subsystem.
  • [0055]
    Short_Term_Pulse_Amp_Ratio—Quantifies last pulse amplitude compared to previous pulse amplitude.
  • [0056]
    Outputs
  • [0057]
    Frequency_Ratio—Ratio of Mean_IR_Frequency_Content to pulse rate.
  • [0058]
    LPF_RoR_Variance—Quantifies variability of ratio-of-ratios. Computed over a 9-second window from LPF_Scaled_Waveforms.
  • [0059]
    Rate_LPF_Weight—Lowpass filter weight to be used by the instance of the Ensemble Averaging subsystem that preprocesses waveforms used for pulse qualification and pulse rate calculation.
  • [0060]
    RoR_Variance—Quantifies variability of ratio-of-ratios. Computed over a 9-second window from Scaled_Waveforms. For example, a value of 0.10 would indicate that sample-to-sample ratio-of-ratios values differ from the mean ratio-of-ratios value by an average of 10% of the mean ratio-of-ratios value.
  • [0061]
    Sat_Ensemble_Averaging_Filter_Weight—Ensemble-averaging weight to be used by the instance of the Ensemble Averaging subsystem that preprocesses waveforms used for pulse qualification and pulse rate calculation.
  • [0062]
    Sat_LPF_Weight—Lowpass filter weight to be used by the instance of the Ensemble Averaging subsystem that preprocesses waveforms used for pulse qualification and pulse rate calculation.
  • [0063]
    Scaled_Waveforms—Scaled versions of IR and Red Pre_Processed_Waveforms.
  • [0064]
    Short_RoR_Variance—Quantifies variability of ratio-of-ratios. Computed over a 3-second window from Scaled_Waveforms.
  • [0065]
    Internal Variables
  • [0066]
    Arr_Prob—Likelihood of arrhythmia that would limit the amount of ensemble averaging. Based on Period_Var, with threshold that are specific to each of the two Ensemble_Averaging_Filter_Weights.
  • [0067]
    Arr_Min_Filt_Wt_For_Rate, Arr_Min_Filt_Wt_For_Sat—Minimum values for the two Ensemble_Averaging_Fiter_Weights, based on their respective Arr_Prob values.
  • [0068]
    LPF_Scaled_Waveforms—Lowpass-filtered version of Scaled_Waveforms, used to compute LPF_RoR_Variance.
  • [0069]
    Mean_IR_Frequency_Content—Estimate of mean frequency content of the IR input waveform. Used to compute Frequency_Ratio metric.
  • [0070]
    RoR_Variance_Based_Filt_Wt—Component for Ensemble_Averaging_Filter_Weights based on RoR_Variance metrics and Long_Term_Pulse_Amp_Ratio.
  • [0071]
    Accordingly, as will be understood by those of skill in the art, the present invention which is related to the selection of ensemble averaging weights, may be embodied in other specific forms without departing from the essential characteristics thereof. For example, while the present embodiments have been described in the time-domain, frequency-based methods are equally relevant to the embodiments of the present invention. Accordingly, the foregoing disclosure is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.
Citas de patentes
Patente citada Fecha de presentación Fecha de publicación Solicitante Título
US3638640 *1 Nov 19671 Feb 1972Robert F ShawOximeter and method for in vivo determination of oxygen saturation in blood using three or more different wavelengths
US3647299 *20 Abr 19707 Mar 1972American Optical CorpOximeter
US4086915 *24 May 19762 May 1978Harvey I. KofskyEar oximetry process and apparatus
US4266554 *19 Jun 197912 May 1981Minolta Camera Kabushiki KaishaDigital oximeter
US4649505 *2 Jul 198410 Mar 1987General Electric CompanyTwo-input crosstalk-resistant adaptive noise canceller
US4723294 *8 Dic 19862 Feb 1988Nec CorporationNoise canceling system
US4799493 *13 Mar 198724 Ene 1989Cardiac Pacemakers, Inc.Dual channel coherent fibrillation detection system
US4800495 *18 Ago 198624 Ene 1989Physio-Control CorporationMethod and apparatus for processing signals used in oximetry
US4802486 *7 Jun 19857 Feb 1989Nellcor IncorporatedMethod and apparatus for detecting optical pulses
US4805623 *4 Sep 198721 Feb 1989Vander CorporationSpectrophotometric method for quantitatively determining the concentration of a dilute component in a light- or other radiation-scattering environment
US4807631 *9 Oct 198728 Feb 1989Critikon, Inc.Pulse oximetry system
US4817013 *17 Oct 198628 Mar 1989Nellcor, Inc.Multichannel gas analyzer and method of use
US4819752 *2 Oct 198711 Abr 1989Datascope Corp.Blood constituent measuring device and method
US4824242 *26 Sep 198625 Abr 1989Sensormedics CorporationNon-invasive oximeter and method
US4892101 *24 Feb 19899 Ene 1990Physio-Control CorporationMethod and apparatus for offsetting baseline portion of oximeter signal
US4907594 *22 Jun 198813 Mar 1990Nicolay GmbhMethod for the determination of the saturation of the blood of a living organism with oxygen and electronic circuit for performing this method
US4911167 *30 Mar 198827 Mar 1990Nellcor IncorporatedMethod and apparatus for detecting optical pulses
US4913150 *18 Ago 19863 Abr 1990Physio-Control CorporationMethod and apparatus for the automatic calibration of signals employed in oximetry
US4927264 *1 Dic 198822 May 1990Omron Tateisi Electronics Co.Non-invasive measuring method and apparatus of blood constituents
US4928692 *23 Nov 198829 May 1990Goodman David EMethod and apparatus for detecting optical pulses
US5078136 *4 Ago 19897 Ene 1992Nellcor IncorporatedMethod and apparatus for calculating arterial oxygen saturation based plethysmographs including transients
US5084327 *18 Dic 198928 Ene 1992Faber-CastellFluorescent marking liquid
US5190038 *1 Nov 19892 Mar 1993Novametrix Medical Systems, Inc.Pulse oximeter with improved accuracy and response time
US5275159 *20 Mar 19924 Ene 1994Madaus Schwarzer Medizintechnik Gmbh & Co. KgMethod and apparatus for diagnosis of sleep disorders
US5279295 *20 Nov 199018 Ene 1994U.S. Philips CorporationNon-invasive oximeter arrangement
US5285782 *17 Ene 199215 Feb 1994Physio-Control CorporationMethod and apparatus for improving the accuracy of pulse transmittance oximeter
US5297548 *12 Abr 199329 Mar 1994Ohmeda Inc.Arterial blood monitoring probe
US5385143 *5 Feb 199331 Ene 1995Nihon Kohden CorporationApparatus for measuring predetermined data of living tissue
US5390670 *20 Oct 199321 Feb 1995Gould Electronics Inc.Flexible printed circuit sensor assembly for detecting optical pulses
US5398680 *8 Jul 199221 Mar 1995Polson; Michael J. R.Pulse oximeter with improved accuracy and response time
US5398682 *15 Nov 199321 Mar 1995Lynn; Lawrence A.Method and apparatus for the diagnosis of sleep apnea utilizing a single interface with a human body part
US5479922 *29 Oct 19932 Ene 1996Del Mar AvionicsBidirectional filter
US5482036 *26 May 19949 Ene 1996Masimo CorporationSignal processing apparatus and method
US5485847 *8 Oct 199323 Ene 1996Nellcor Puritan Bennett IncorporatedPulse oximeter using a virtual trigger for heart rate synchronization
US5490505 *6 Oct 199313 Feb 1996Masimo CorporationSignal processing apparatus
US5494032 *23 May 199427 Feb 1996Sandia CorporationOximeter for reliable clinical determination of blood oxygen saturation in a fetus
US5503148 *1 Nov 19942 Abr 1996Ohmeda Inc.System for pulse oximetry SPO2 determination
US5511042 *25 May 199523 Abr 1996The United States Of America As Represented By The Secretary Of The NavyEnhanced adaptive statistical filter providing improved performance for target motion analysis noise discrimination
US5605151 *21 Feb 199525 Feb 1997Lynn; Lawrence A.Method for the diagnosis of sleep apnea
US5611337 *28 Abr 199518 Mar 1997Hewlett-Packard CompanyPulsoximetry ear sensor
US5730124 *14 Dic 199424 Mar 1998Mochida Pharmaceutical Co., Ltd.Medical measurement apparatus
US5743263 *5 Oct 199528 Abr 1998Nellcor Puritan Bennett IncorporatedPulse Oximeter using a virtual trigger for heart rate synchronization
US5871442 *19 May 199716 Feb 1999International Diagnostics Technologies, Inc.Photonic molecular probe
US5873821 *18 May 199223 Feb 1999Non-Invasive Technology, Inc.Lateralization spectrophotometer
US6011986 *2 Feb 19984 Ene 2000Masimo CorporationManual and automatic probe calibration
US6181958 *5 Feb 199930 Ene 2001In-Line Diagnostics CorporationMethod and apparatus for non-invasive blood constituent monitoring
US6181959 *26 Mar 199730 Ene 2001Kontron Instruments AgDetection of parasitic signals during pulsoxymetric measurement
US6339715 *30 Sep 199915 Ene 2002Ob ScientificMethod and apparatus for processing a physiological signal
US6353750 *24 Jun 19985 Mar 2002Sysmex CorporationLiving body inspecting apparatus and noninvasive blood analyzer using the same
US6360114 *21 Mar 200019 Mar 2002Masimo CorporationPulse oximeter probe-off detector
US6505060 *29 Sep 20007 Ene 2003Datex-Ohmeda, Inc.Method and apparatus for determining pulse oximetry differential values
US6526301 *19 Dic 200025 Feb 2003Criticare Systems, Inc.Direct to digital oximeter and method for calculating oxygenation levels
US6544193 *23 Feb 20018 Abr 2003Marcio Marc AbreuNoninvasive measurement of chemical substances
US6546267 *27 Nov 20008 Abr 2003Nihon Kohden CorporationBiological sensor
US6549795 *14 Jul 199815 Abr 2003Non-Invasive Technology, Inc.Spectrophotometer for tissue examination
US6678543 *8 Nov 200113 Ene 2004Masimo CorporationOptical probe and positioning wrap
US6684090 *15 May 200127 Ene 2004Masimo CorporationPulse oximetry data confidence indicator
US6690958 *7 May 200210 Feb 2004Nostix LlcUltrasound-guided near infrared spectrophotometer
US6697658 *26 Jun 200224 Feb 2004Masimo CorporationLow power pulse oximeter
US6708048 *13 Ene 199916 Mar 2004Non-Invasive Technology, Inc.Phase modulation spectrophotometric apparatus
US6711424 *22 Dic 199923 Mar 2004Orsense Ltd.Method of optical measurement for determing various parameters of the patient's blood
US6711425 *28 May 200223 Mar 2004Ob Scientific, Inc.Pulse oximeter with calibration stabilization
US6714245 *16 Mar 199930 Mar 2004Canon Kabushiki KaishaVideo camera having a liquid-crystal monitor with controllable backlight
US6721584 *6 Jun 200113 Abr 2004Nellcor Puritan Bennett IncorporatedMethod and apparatus for estimating physiological parameters using model-based adaptive filtering
US6839582 *12 Ago 20024 Ene 2005Datex-Ohmeda, Inc.Pulse oximetry method and system with improved motion correction
US6850053 *7 Ago 20021 Feb 2005Siemens AktiengesellschaftDevice for measuring the motion of a conducting body through magnetic induction
US6863652 *10 Mar 20038 Mar 2005Draeger Medical Systems, Inc.Power conserving adaptive control system for generating signal in portable medical devices
US6873865 *12 Dic 200329 Mar 2005Hema Metrics, Inc.Method and apparatus for non-invasive blood constituent monitoring
US6983178 *15 Mar 20013 Ene 2006Orsense Ltd.Probe for use in non-invasive measurements of blood related parameters
US6987994 *3 Nov 200317 Ene 2006Datex-Ohmeda, Inc.Pulse oximetry SpO2 determination
US6993371 *22 Jul 200331 Ene 2006Masimo CorporationPulse oximetry sensor adaptor
US6996427 *18 Dic 20037 Feb 2006Masimo CorporationPulse oximetry data confidence indicator
US7024235 *30 Dic 20034 Abr 2006University Of Florida Research Foundation, Inc.Specially configured nasal pulse oximeter/photoplethysmography probes, and combined nasal probe/cannula, selectively with sampler for capnography, and covering sleeves for same
US7027849 *21 Nov 200311 Abr 2006Masimo Laboratories, Inc.Blood parameter measurement system
US7030749 *28 Oct 200418 Abr 2006Masimo CorporationParallel measurement alarm processor
US7035697 *22 Feb 200525 Abr 2006Roy-G-Biv CorporationAccess control systems and methods for motion control
US7162306 *19 Nov 20019 Ene 2007Medtronic Physio - Control Corp.Internal medical device communication bus
US7209774 *27 Abr 200624 Abr 2007Nellcor Puritan Bennett IncorporatedPulse oximeter with separate ensemble averaging for oxygen saturation and heart rate
US7209775 *15 Abr 200424 Abr 2007Samsung Electronics Co., Ltd.Ear type apparatus for measuring a bio signal and measuring method therefor
US20020026106 *18 May 199828 Feb 2002Abbots LaboratoriesNon-invasive sensor having controllable temperature feature
US20020035318 *16 Abr 200121 Mar 2002Mannheimer Paul D.Pulse oximeter sensor with piece-wise function
US20020038079 *13 Jun 200128 Mar 2002Steuer Robert R.System for noninvasive hematocrit monitoring
US20020042558 *24 Ago 200111 Abr 2002Cybro Medical Ltd.Pulse oximeter and method of operation
US20020049389 *23 Feb 200125 Abr 2002Abreu Marcio MarcNoninvasive measurement of chemical substances
US20030009091 *6 Ago 20029 Ene 2003Edgar Reuben W.Method, apparatus and system for removing motion artifacts from measurements of bodily parameters
US20030023140 *18 Jun 200230 Ene 2003Britton ChancePathlength corrected oximeter and the like
US20030055324 *17 Oct 200120 Mar 2003Imagyn Medical Technologies, Inc.Signal processing method and device for signal-to-noise improvement
US20030060693 *25 Jun 200227 Mar 2003Monfre Stephen L.Apparatus and method for quantification of tissue hydration using diffuse reflectance spectroscopy
US20040010188 *19 Jun 200315 Ene 2004Yoram WassermanSignal processing method and device for signal-to-noise improvement
US20040039273 *21 Ago 200326 Feb 2004Terry Alvin MarkCepstral domain pulse oximetry
US20040054270 *25 Sep 200118 Mar 2004Eliahu PewznerApparatus and method for monitoring tissue vitality parameters
US20050080323 *11 Ago 200414 Abr 2005Toshinori KatoApparatus for evaluating biological function
US20060009688 *27 May 200512 Ene 2006Lamego Marcelo MMulti-wavelength physiological monitor
US20060015021 *29 Jun 200419 Ene 2006Xuefeng ChengOptical apparatus and method of use for non-invasive tomographic scan of biological tissues
US20060020181 *30 Sep 200526 Ene 2006Schmitt Joseph MDevice and method for monitoring body fluid and electrolyte disorders
US20060030763 *30 Sep 20059 Feb 2006Nellcor Puritan Bennett IncorporatedPulse oximeter sensor with piece-wise function
US20060052680 *31 Oct 20059 Mar 2006Diab Mohamed KPulse and active pulse spectraphotometry
US20060058683 *13 Ago 200516 Mar 2006Britton ChanceOptical examination of biological tissue using non-contact irradiation and detection
US20060064024 *18 Ene 200523 Mar 2006Schnall Robert PBody surface probe, apparatus and method for non-invasively detecting medical conditions
Citada por
Patente citante Fecha de presentación Fecha de publicación Solicitante Título
US9050043 *4 May 20109 Jun 2015Nellcor Puritan Bennett IrelandSystems and methods for wavelet transform scale-dependent multiple-archetyping
US20110270048 *30 Abr 20103 Nov 2011Nellcor Puritan Bennett IrelandSystems and methods for ppg sensors incorporating ekg sensors
US20110276275 *4 May 201010 Nov 2011Nellcor Puritan Bennett IrelandSystems And Methods For Wavelet Transform Scale-Dependent Multiple-Archetyping
Clasificaciones
Clasificación de EE.UU.600/324
Clasificación internacionalA61B5/00, A61B5/1455
Clasificación cooperativaA61B5/7221, A61B5/7203, A61B5/14552
Clasificación europeaA61B5/1455N, A61B5/72D
Eventos legales
FechaCódigoEventoDescripción
28 Dic 2010ASAssignment
Owner name: NELLCOR PURITAN BENNETT INCORPORATED, CALIFORNIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:BAKER, CLARK R., JR.;REEL/FRAME:025545/0389
Effective date: 20040628
5 Nov 2012ASAssignment
Owner name: NELLCOR PURITAN BENNETT LLC, COLORADO
Free format text: CHANGE OF NAME;ASSIGNOR:NELLCOR PURITAN BENNETT INCORPORATED;REEL/FRAME:029247/0329
Effective date: 20061220
20 Nov 2012ASAssignment
Owner name: COVIDIEN LP, MASSACHUSETTS
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:NELLCOR PURITAN BENNETT LLC;REEL/FRAME:029330/0561
Effective date: 20120929
15 Ago 2014FPAYFee payment
Year of fee payment: 4